Background

Most of the work I do consists of churning undefined (but structured) datasets and generating meaningful information and trends - i.e., Data Analysis, Knowledge Discovery, and Trend Analysis. And as such, most of the data I get are never really similar. In situations like these, you need to come up with a generic way of doing basic stuff like data presentations (reporting) for any kind of dataset. This led me to create a DataMatrix a long time ago. But as we all know, it is not very obvious how to handle anonymous data in WPF.

I know I could have just used a regular DataTable and bound it to the WPF DataGrid, but I can assure you, when you deal with millions of records that cannot be virutalized, a DataTable becomes very heavy, hogs memory, and results in too much messy code [behind] with "Magic" strings all over the place. Besides, we have to keep things as M-V-VM as possible.

Using the Code

Basically, what we are going to do is bind a ListView to a DataMatrix class as shown below:

Note that the MatrixColumn can always be extended with all the properties you need to format the GridViewColumns.

To achieve this, we need to create a DependencyProperty which will be added to the ListView so that when the DataMatrixSource is set, we can then bind the undefined columns to the ListView at runtime. Below is the class that contains the DependencyProperty.

And that's all. At runtime, your columns will be added dynamically to the ListView's GridView. Note that the ListView's ItemsSource property expects an IEnumerable as the binding element; that is why the matrix implements this interface. This is provided by the GenericEnumerator shown below:

For this example, I used the generic Northwind database and bound to the Orders table (orders count per month/year); then I built a simple DataMatrix from the cross tabulation of the Year (row source) vs. Months (columns source) against the sum for the number of orders.

Given the Orders table, you can generate and bind to a well-known dataset to get the "Number of Orders per Month" as follows:

To get a more meaningful dataset from the above query, we need to cross-tabulate the year vs. month to get the total number of orders. So, we can run the dataset through a reporting algorithm and generate a DataMatrix as follows:

Note: This is a fakeDataMatrixGenerator. A real one will determine the columns (at runtime) based on the parameters specified.